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ICDE
2006
IEEE
176views Database» more  ICDE 2006»
13 years 10 months ago
Deriving Private Information from Perturbed Data Using IQR Based Approach
Several randomized techniques have been proposed for privacy preserving data mining of continuous data. These approaches generally attempt to hide the sensitive data by randomly m...
Songtao Guo, Xintao Wu, Yingjiu Li
PAKDD
2007
ACM
130views Data Mining» more  PAKDD 2007»
13 years 10 months ago
Deriving Private Information from Arbitrarily Projected Data
Distance-preserving projection based perturbation has gained much attention in privacy-preserving data mining in recent years since it mitigates the privacy/accuracy tradeoff by ac...
Songtao Guo, Xintao Wu
ICDE
2009
IEEE
192views Database» more  ICDE 2009»
14 years 6 months ago
Deriving Private Information from Association Rule Mining Results
Data publishing can provide enormous benefits to the society. However, due to privacy concerns, data cannot be published in their original forms. Two types of data publishing can a...
Zutao Zhu, Guan Wang, Wenliang Du
SIGMOD
2005
ACM
128views Database» more  SIGMOD 2005»
14 years 4 months ago
Deriving Private Information from Randomized Data
Randomization has emerged as a useful technique for data disguising in privacy-preserving data mining. Its privacy properties have been studied in a number of papers. Kargupta et ...
Zhengli Huang, Wenliang Du, Biao Chen
SAC
2006
ACM
13 years 10 months ago
On the use of spectral filtering for privacy preserving data mining
Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining.The previous work based on spectral filtering, show the noise ma...
Songtao Guo, Xintao Wu